Crunchbase is the de facto database of the startup world. Over 3 million company profiles, more than 600,000 funding rounds, and an investor graph that VCs, founders, and analysts treat as ground truth. The data sits behind a login wall, a heavy JavaScript frontend, and an enterprise API that prices most teams out of the market.
This post covers what data lives on Crunchbase, why it's hard to get programmatically, who needs it, and how to run our actor to extract it without building or maintaining any scraping infrastructure.
Why Crunchbase data is hard to get
The official API is enterprise-only. Crunchbase's Enterprise API starts around $49,000/year and requires an annual contract. The cheaper Pro subscription gives you a web UI and CSV exports, but no programmatic access for automation. There is no developer tier — the company has explicitly chosen to monetize data access at the top of the funnel. For a solo founder, an analyst at a small fund, or a data team building an internal CRM enrichment, the API simply isn't an option.
Most of the interesting data is behind a login. Public visitors see a stripped-down version of company pages. Funding round details, investor lists, key employees, acquisition history, and competitor data require an authenticated session. That single architectural choice eliminates 90% of naive scraping approaches — you can't just curl a profile URL and parse the HTML.
The frontend is heavy and dynamic. Crunchbase is a single-page React-style application. Profile data loads asynchronously through internal GraphQL-style endpoints, with request signing and session-bound tokens. The HTML you get on first paint contains almost no real data — it's a shell that hydrates client-side. Headless browsers can render it, but each profile takes seconds and significant compute, and the anti-bot stack flags automated browsers quickly.
The anti-bot stack is real. Cloudflare bot management, behavioral fingerprinting, request rate analysis, and aggressive IP reputation scoring all run on Crunchbase. A datacenter IP gets challenged within a few requests. Even residential proxies need careful rotation to avoid the heuristics that look for unnatural session patterns. This is a moving target — what worked last month often breaks this month.
The result: most teams either pay for Crunchbase Pro and copy-paste manually, license bulk data from resellers, or quietly maintain a fragile in-house scraper. None of these are ideal.
Who actually needs this data
VC and angel investor research. Before a partner meeting, an associate needs to pull funding history, current valuation signals, investor syndicate, key team members, and competitor landscape for a target company. Doing this manually across a pipeline of 50 deals per week is hours of clicking. Automated extraction turns it into a single overnight run.
Competitive intelligence. Mapping a competitive landscape means pulling funding rounds, headcount trajectories, and acquisition history for 20-100 companies in a sector. The funding round data alone — who invested, at what stage, when — is the spine of any defensible competitive analysis.
Sales enrichment for B2B targeting AI/SaaS startups. A sales team selling tools to Series A-C startups needs filtered lists by funding stage, last round date, total raised, and investor list. Crunchbase is where this data is most current and most accurate. Enriching a prospect list with last-funding signals lets sales prioritize companies likely to have budget right now.
M&A and corporate development. Corp dev teams scanning the market for acquisition targets pull acquisition history, funding totals, and founder backgrounds at scale. The investor list on a target also signals which firms might block or push a deal.
Market research and analyst reports. Researchers writing sector reports — fintech, climate tech, AI infrastructure — need bulk data on hundreds of companies in a category. Funding round data over time is the raw material for "where is the money flowing" charts that anchor most industry reports.
Founder competitive due diligence. Before raising, founders benchmark themselves against competitors: how much each raised, from whom, on what trajectory. Walking into a partner meeting with this data prepared is table stakes now.
What data you actually get
Our actor extracts the following fields from public and authenticated Crunchbase company profiles:
- name — official company name
- crunchbase_url — canonical Crunchbase profile URL
- description — short and long company descriptions
- website — official company website
- founded_date — founding date as listed
- headquarters — city, region, country
- industries — list of industry categories
- operating_status — active, closed, acquired
- company_type — for profit, non-profit, etc.
- employee_count — headcount range
- total_funding — total funding raised in USD
- last_funding_round — type, date, and amount of most recent round
- funding_rounds — full list of funding rounds with stage, date, amount, and lead investors
- investors — list of investor entities with name, type, and lead/follow flag
- founders — founder names and roles
- key_people — current executives and key employees
- acquisitions — companies acquired, with dates and disclosed amounts
- acquired_by — acquirer details if the company was acquired
- competitors — competitor list as listed on the profile
- scraped_at — extraction timestamp
How to run the actor
Via Apify Console (no code needed):
- Go to apify.com/cryptosignals/crunchbase-scraper
- Click Try for free
- Paste your company list into the
companiesfield — accepts Crunchbase slugs (e.g.,stripe) or full profile URLs - Set
max_resultsto cap the run if you're testing - Click Start and download results as JSON or CSV
Input JSON:
{
"companies": [
"stripe",
"https://www.crunchbase.com/organization/anthropic",
"openai"
],
"include_funding_rounds": true,
"include_investors": true,
"max_results": 50
}
Via Apify API:
curl -X POST "https://api.apify.com/v2/acts/cryptosignals~crunchbase-scraper/runs" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_APIFY_TOKEN" \
-d '{
"companies": ["stripe", "anthropic"],
"include_funding_rounds": true,
"max_results": 10
}'
Sample output record:
{
"name": "Anthropic",
"crunchbase_url": "https://www.crunchbase.com/organization/anthropic",
"description": "AI safety company building reliable, interpretable AI systems.",
"website": "https://anthropic.com",
"founded_date": "2021-01-01",
"headquarters": "San Francisco, California, US",
"industries": ["Artificial Intelligence", "Machine Learning", "Software"],
"operating_status": "Active",
"company_type": "For Profit",
"employee_count": "501-1000",
"total_funding": 7600000000,
"last_funding_round": {
"type": "Series E",
"date": "2025-03-01",
"amount": 3500000000
},
"funding_rounds": [
{"type": "Series A", "date": "2021-05-01", "amount": 124000000, "lead_investors": ["Jaan Tallinn"]},
{"type": "Series B", "date": "2022-04-01", "amount": 580000000, "lead_investors": ["Sam Bankman-Fried"]},
{"type": "Series C", "date": "2023-05-01", "amount": 450000000, "lead_investors": ["Spark Capital"]}
],
"investors": [
{"name": "Google", "type": "corporate", "lead": true},
{"name": "Spark Capital", "type": "vc", "lead": true},
{"name": "Salesforce Ventures", "type": "corporate", "lead": false}
],
"founders": [
{"name": "Dario Amodei", "role": "CEO"},
{"name": "Daniela Amodei", "role": "President"}
],
"scraped_at": "2026-05-04T09:00:00+00:00"
}
Pricing
The actor uses pay-per-event pricing: $0.012 per company profile with funding rounds and investors included. The first 3 results are free so you can verify output quality before committing. For a list of 1,000 companies, that's $12.
For high-volume runs, residential proxy coverage matters for reliability. Oxylabs is the proxy infrastructure we've tested for this kind of workload — their residential network handles Crunchbase's reputation scoring without the constant rotation failures that plague datacenter proxies.
What you don't get
Crunchbase profiles don't include private company financials beyond disclosed funding rounds, employee email addresses, or anything behind Crunchbase Pro's premium signals (e.g., predictive scores). For contact-level data on individuals at these companies, you need a separate enrichment step.
The actor extracts what's available on the standard profile page. Some very large or very recently created companies have partial data on Crunchbase itself — that's a Crunchbase coverage limit, not an extraction limit.
The alternative
You can build this yourself. The engineering work involves: managing an authenticated session that doesn't get flagged, handling Crunchbase's anti-bot stack, parsing the React-hydrated data without depending on internal endpoints that change, building proxy rotation and retry logic, and maintaining the whole thing as Crunchbase pushes frontend updates — which happens often.
That's 3-6 weeks of engineering time to build something reliable, plus ongoing maintenance. At $0.012 per company, you'd need to scrape over 2.5 million profiles before the build-vs-buy math favors building. Crunchbase has 3 million profiles total, so realistically you never cross that line.
For most teams the answer is clear: don't build it.
Actor: apify.com/cryptosignals/crunchbase-scraper
By: Web Data Labs — data infrastructure for B2B and investor teams.
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